Inspiration

I used to work at a call center. The biggest problem we have is call volume. Having a chatbot would greatly reduce a call center operator's workload and stress. We decided to develop a chatbot to be the first contact for vacation inquiries.

What it does

Handles common vacation inquiries and assess if escalation to a human operator is required. It uses various machine learning models in the backend to generate replies and assess if escalation is required.

How we built it

Front End

  • React (cra)
  • css, Bulma, animate.css

Back End

  • Flask
  • seq2seq

Challenges we ran into

Overfitting

Our model overfit the data and produced predictable results. We tried additional models to augment our chatbot and provide a better response.

Deployment

App worked locally but failed on Azure. After consulting documentation and asking around, managed to locate logging information on Azure portal and realized a dependency was missing for the flask application.Ultimately we did not manage to deploy our model on azure.

What I learned

  • flexbox, css animation, responsive design

Built With

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